Our August Issue is now available online! Featuring methods for monitoring deep sea benthic habitats, simulating host–symbiont evolution, measuring microclimates & many more!

Read on to discover our featured articles, specially selected by Senior Editor Aaron Ellison, plus find out more about the Applications and Practical Tools articles we have in this issue.

Featured Articles

treeducken *open access* Cophylogenetic methods describe discordance between non-independent phylogenies. Simulation is necessary for testing these methods, but few simulators exist that are capable of generating data under explicit and biologically meaningful models. Here, Dismukes & Heath present treeducken, an R package for simulating host–symbiont evolution and gene-tree–species-tree evolution.

The Azor drift-cam *open access* The increasing need to gather large-scale data on the distribution and conservation status of deep-sea benthic species and habitats could benefit from the availability of low-cost imaging tools to facilitate the access to the deep sea world-wide. Here, Dominguez-Carrió et al. describe the Azor drift-cam, a cost-effective video platform designed to conduct rapid appraisals of deep-sea benthic habitats. This drift-cam system has the potential to make deep-sea exploration more accessible, playing an important role in the Deep-Ocean Observing Strategy and measuring some of the Essential Ocean Variables for deep-sea monitoring and conservation strategies.

Measuring microclimate *open access* Maclean et al. address the problem of accurately measuring temperatures in microenvironments. They first discuss the theory of measuring surface, ground and air temperatures with reference to energy fluxes and how these are modified by material, reflective properties and size of the device. They highlight the particular difficulties associated with measuring air temperature and report on the results of a series of experiments in which air temperatures recorded by various commonly used microclimate temperature loggers are compared to those obtained using research-grade instruments and synoptic weather stations.

Infectious disease phylodynamics With the increasing genomic surveillance of pathogens, especially during the SARS-CoV-2 pandemic, new practical questions about the use of phylodynamic models are emerging. One such question focuses on the inclusion of unsequenced case occurrence data alongside sequenced data to improve phylodynamic analyses. This approach can be particularly valuable if sequencing efforts vary over time. Using simulations, Featherstone et al. demonstrate here that birth–death phylodynamic models can employ occurrence data to eliminate bias in estimates of the basic reproductive number due to misspecification of the sampling process.

Understanding the reliability of citizen science Citizen science projects have become increasingly popular in many fields, including ecology. However, the quality of this information is frequently debated within the scientific community. Modern citizen science implementations therefore require measures of the users’ proficiency. Here, Santos-Fernandez, & Mengersen introduce a new methodological framework of item response that quantifies a citizen scientist’s ability, taking into account the difficulty of the task.


GenomeAdmixR *open access* Hybridisation and other types of genome admixture have received increasing attention for their implications in speciation, human evolution, Evolve and Resequence (E&R) and genetic mapping. However, a thorough understanding of how local ancestry changes after admixture and how selection affects patterns of local ancestry remains elusive. Here, Janzen & Diaz present the R package GenomeAdmixR, which uses an individual-based model to simulate genomic patterns following admixture forward in time. GenomeAdmixR provides user-friendly functions to set up and analyse simulations under evolutionary scenarios with selection, linkage and migration.

FRaME *free access* Floral fire ecology incorporates a feedback loop in which plants influence fire behaviour and fire behaviour influences the flora. Recent advances in fire behaviour modelling have quantified many plant-based drivers of fire behaviour, but the consequent ecological effects have not been adequately modelled mechanistically. Here, Philip Zylstra introduces the R package Fire Research and Modelling Environment (FRaME), which calculates the influence of plants on fire behaviour using a biophysical, mechanistic model of fire behaviour, building this into complex simulations. From these, it models heat transfer from flames into surrounding surfaces, calculating its ecological effects on plants and soils.

Practical Tools

PICT *open access* Commercial camera traps (CTs) commonly used in wildlife studies have several limitations; they are not easily customisable, unit prices sharply increase with image quality and they are not designed to record the activity of ectotherms such as insects. Those developed for the study of plant–insect interactions are yet to be widely adopted as they rely on expensive and heavy equipment. Here, Droissart et al. developed PICT (plant–insect interactions camera trap), an inexpensive CT system based on a Raspberry Pi Zero computer designed to continuously film animal activity. The system is particularly well suited for the study of pollination, insect behaviour and predator–prey interactions.

The Ants on the Cover

This issue’s cover shows two Camponotus sanctus ants performing trophallaxis, the social sharing of food. In many species of social insects, an elaborate network of trophallactic interactions is the main means to distribute nutrients and physiological regulatory signals between individuals. Tracking the flows of nutrients throughout the colony is important for gaining mechanistic understanding of the collective regulation of nutrition and development. In their article, Baltiansky et al. present a dual-fluorescence imaging system that allows one to quantitatively track the simultaneous distribution of two materials throughout the colony. In addition, they present a deep neural network for the automatic detection of ant trophallaxis events. Together, these advances serve as an efficient, non-disruptive way to observe the inner-workings of colonies of social insects. Photo credit: ©Dr. Ehud Fonio.